class_docstr: `AutoMLStep` for SageMaker Pipelines Workflows.
class_docstr_tok: ["`","AutoMLStep","`","for","SageMaker","Pipelines","Workflows","."]
docstr: The arguments dictionary that is used to call `create_auto_ml_job`.
  
  NOTE: The `CreateAutoMLJob` request is not quite the
      args list that workflow needs.
  
  `ModelDeployConfig` and `GenerateCandidateDefinitionsOnly`
      attribute cannot be included.
docstr_tok: ["The","arguments","dictionary","that","is","used","to","call","`","create_auto_ml_job","`",".","NOTE",":","The","`","CreateAutoMLJob","`","request","is","not","quite","the","args","list","that","workflow","needs",".","`","ModelDeployConfig","`","and","`","GenerateCandidateDefinitionsOnly","`","attribute","can","not","be","included","."]
code: def arguments(self) -> RequestType:
      """The arguments dictionary that is used to call `create_auto_ml_job`.
  
      NOTE: The `CreateAutoMLJob` request is not quite the
          args list that workflow needs.
  
      `ModelDeployConfig` and `GenerateCandidateDefinitionsOnly`
          attribute cannot be included.
      """
      from sagemaker.workflow.utilities import execute_job_functions
      from sagemaker.workflow.utilities import _pipeline_config
  
      # execute fit function in AutoML with saved parameters,
      # and store args in PipelineSession's _context
      execute_job_functions(self.step_args)
  
      # populate request dict with args
      auto_ml = self.step_args.func_args[0]
      request_dict = auto_ml.sagemaker_session.context.args
  
      if "AutoMLJobConfig" not in request_dict:
          raise AutoMLStepInvalidModeError()
      if (
          "Mode" not in request_dict["AutoMLJobConfig"]
          or request_dict["AutoMLJobConfig"]["Mode"] != "ENSEMBLING"
      ):
          raise AutoMLStepInvalidModeError()
  
      if "ModelDeployConfig" in request_dict:
          request_dict.pop("ModelDeployConfig", None)
      if "GenerateCandidateDefinitionsOnly" in request_dict:
          request_dict.pop("GenerateCandidateDefinitionsOnly", None)
      # Continue to pop job name if not explicitly opted-in via config
      # AutoML Trims to AutoMLJo-2023-06-23-22-57-39-083
      request_dict = trim_request_dict(
          request_dict, "AutoMLJobName", _pipeline_config
      )
  
      return request_dict
  
file_path: sagemaker-python-sdk/src/sagemaker/workflow/automl_step.py
imports: from __future__ import absolute_import
  from typing import Union, Optional, List
  from sagemaker import Session, Model
  from sagemaker.exceptions import AutoMLStepInvalidModeError
  from sagemaker.workflow.entities import RequestType
  from sagemaker.workflow.pipeline_context import _JobStepArguments
  from sagemaker.workflow.properties import Properties
  from sagemaker.workflow.retry import RetryPolicy
  from sagemaker.workflow.steps import ConfigurableRetryStep, CacheConfig, Step, StepTypeEnum
  from sagemaker.workflow.utilities import validate_step_args_input, trim_request_dict
  from sagemaker.workflow.step_collections import StepCollection
label_desc: Use image node_id 2 for calling the AutoMLStep obj's underlying member method code with example usage: obj.arguments() and returns: request_dict